arXiv:2605.28405v1 Announce Type: new Abstract: Despite widespread discussion of AGI, there is no clear framework for measuring progress toward it. This ambiguity fuels subjective claims, makes it difficult to track progress, and risks hindering responsible governance. As a starting point to address this gap, we present a framework for understanding system capabilities in relation to human cognitive abilities. Drawing from decades of research in psychology, neuroscience, and cognitive science, we introduce a Cognitive Taxonomy that deconstructs general intelligence into 10 key cognitive facult
The proliferation of advanced AI models and widespread discussion of AGI necessitates a structured approach to measuring progress to prevent ambiguity and enable responsible development.
A clear framework for AGI measurement is crucial for guiding research, assessing actual capabilities, and informing policy decisions regarding AI deployment and governance.
This framework shifts AGI discussion from subjective claims to a more objective, cognitively-rooted understanding of system capabilities, potentially standardizing evaluation metrics.
- · AI researchers
- · Policymakers
- · AI ethics organizations
- · Companies making unsubstantiated AGI claims
- · Uncritical AI enthusiasts
- · AI evaluators lacking standardized tools
The framework will enable more rigorous and comparative evaluation of AI systems against human cognitive abilities.
Standardized metrics could accelerate AGI research by clarifying target capabilities and identifying specific areas of weakness.
Improved measurement could lead to more effective regulation and governance of advanced AI, reducing risks associated with unbridled development.
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Read at arXiv cs.AI